Breast Cancer Classification using Random Forest Algorithm

Abstract This study uses detect breast cancer based on Random Forest (RF). It is crucial to diagnose the illness identify treatment solutions closely linked patient safety. Breast diagnosed using past medical records and various classification methods used in data mining fields today. Each technique performs differently depending input feature types model parameters. Neutral Networks have been proven be more effective analysis pre-diagnosis without requiring knowledge. The reduces diagnostic variance increases accuracy by overcoming limitation of individual models. had a training validation 90% 91%.